Therapeutic angiogenesis and vasculogenesis for tissue regeneration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Therapeutic angiogenesis/vasculogenesis holds promise for the cure of ischaemic disease. The approach postulates the manipulation of spontaneous healing response by supplementation of growth factors or transplantation of vascular progenitor cells. These supplements are intended to foster the formation of arterial collaterals and promote the regeneration of damaged tissues. Angiogenic factors are generally delivered in the form of recombinant proteins or by gene transfer using viral vectors. In addition, new non-viral methods are gaining importance for their safer profile. The association of growth factors with different biological activity might offer distinct advantages in terms of efficacy, yet combined approaches require further optimization. Alternatively, substances with pleiotropic activity might be considered, by virtue of their ability to target multiple mechanisms. For instance, some angiogenic factors not only stimulate the growth of arterioles and capillaries, but also inhibit vascular destabilization triggered by metabolic and oxidative stress. Transplantation of endothelial progenitor cells was recently proposed for the treatment of peripheral and myocardial ischaemia. Progenitor cells can be transplanted either without any preliminary conditioning or after ex vivo genetic manipulation. Delivery of genetically modified progenitor cells eliminates the drawback of immune response against viral vectors and makes feasible repeating the therapeutic procedure in case of injury recurrence. It is envisioned that these new approaches of regenerative medicine will open unprecedented opportunities for the care of life-threatening diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it